Machine Learning experiments can be cheap and powerful aides for marketers looking to their historical data for predictive qualities which may drive future revenue. However marketers are raised on the religion of data and pray at the altar of A/B testing and focus groups. Marketers don’t need to be convinced of the virtues of data in their decision making, it is preaching to the choir.

However other groups within an organization, such as HR, IT, sales, finance and operations may use descriptive analytics to analyze the past, but often rely on human instincts in their decision making that shapes the future. These groups are often following ‘sacred cow’ business processes defined by HiPPOs that have never been properly analyzed and validated by data experiments.

Imagine an HR leader learning that their program designed to increase employee engagement had no statistically significant impact, and that other factors are more predictive of engaged employees within their organization. This analysis has the potential to be embarrassing to the management team, hence these machine learning experiments are often never performed.

Aside from fear of authority and self-preservation instincts, humans also bring inflexibility or hubris into the workplace that over value their own experience and decision making prowess, which preclude them from exploring new solutions, especially solutions that can not be discovered by another human, like themselves, but require the computing power of machines.

There are many technical reasons why machine learning experiments could fail to find predictive patterns in historical data, but the cultural barriers that prevent companies from even beginning experiments can be most crippling. It takes courage to challenge the status quo and people at the top of management hierarchies. Be courageous and don’t let your organization’s HiPPOs and Sacred Cows stymie your curiosity to experiment with data to find better ways to run your business!